Aristizabal Juan C, Estrada-Restrepo Alejandro, Giraldo García Argenis
Physiology and Biochemistry Research Group-PHYSIS, Universidad de Antioquia, Medellin, Colombia.
School of Nutrition and Dietetics, Universidad de Antioquia, Medellin, Colombia.
Colomb Med (Cali). 2018 Jun 30;49(2):154-159. doi: 10.25100/cm.v49i2.3643.
To develop anthropometric equations to predict body fat percentage (BF%).
In 151 women (aged 18-59) body weight, height, eight- skinfold thickness (STs), six- circumferences (CIs), and BF% by hydrodensitometry were measured. Subjects data were randomly divided in two groups, equation-building group (n= 106) and validation group (n= 45). The equation-building group was used to run linear regression models using anthropometric measurements as predictors to find the best prediction equations of the BF%. The validation group was used to compare the performance of the new equations with those of Durnin-Womersley, Jackson-Pollock and Ramirez-Torun.
There were two preferred equations: Equation 1= 11.76 + (0.324 x tricipital ST) + (0.133 x calf ST) + (0.347 x abdomen CI) + (0.068 x age) - (0.135 x height) and Equation 2= 11.37 + (0.404 x tricipital ST) + (0.153 x axilar ST) + (0.264 x abdomen CI) + (0.069 x age) - (0.099 x height). There were no significant differences in BF% obtained by hydrodensitometry (31.5 ±5.3) and Equation 1 (31.0 ±4.0) and Equation 2 (31.2 ±4.0). The BF% estimated by Durning-Womersley (35.8 ±4.0), Jackson-Pollock (26.5 ±5.4) and Ramirez-Torun (32.6 ±4.8) differed from hydrodensitometry ( <0.05). The interclass correlation coefficient (ICC) was high between hydrodensitometry and Equation 1 (ICC= 0.77), Equation 2 (ICC= 0.76), and Ramirez-Torun equation (ICC= 0.75). The ICC was low between hydrodensitometry and Durnin-Womersley (ICC= 0.51) and Jackson-Pollock (ICC= 0.53) equations.
The new Equations-1 and 2, performed better than the commonly used anthropometric equations to predict BF% in adult women.
建立人体测量学方程以预测体脂百分比(BF%)。
对151名年龄在18 - 59岁的女性测量体重、身高、8处皮褶厚度(STs)、6处周长(CIs)以及通过水下密度测量法测得的BF%。将受试者数据随机分为两组,方程构建组(n = 106)和验证组(n = 45)。方程构建组用于运行线性回归模型,以人体测量学指标作为预测因子来寻找BF%的最佳预测方程。验证组用于比较新方程与杜宁 - 沃姆斯利方程、杰克逊 - 波洛克方程和拉米雷斯 - 托伦方程的性能。
有两个优选方程:方程1 = 11.76 +(0.324×三头肌皮褶厚度)+(0.133×小腿皮褶厚度)+(0.347×腹部周长)+(0.068×年龄) - (0.135×身高);方程2 = 11.37 +(0.404×三头肌皮褶厚度)+(0.153×腋窝皮褶厚度)+(0.264×腹部周长)+(0.069×年龄) - (0.099×身高)。通过水下密度测量法测得的BF%(31.5±5.3)与方程1(31.0±4.0)和方程2(31.2±4.0)之间无显著差异。杜宁 - 沃姆斯利方程(35.8±4.0)、杰克逊 - 波洛克方程(26.